Table of Contents

• Personalized Peer Truth Serum for Eliciting Multi-Attribute Personal DataNaman Goel, Boi Faltings. 1 [doi]
• Conditional Expectation PropagationZheng Wang, Shandian Zhe. 6 [doi]
• A Sparse Representation-Based Approach to Linear Regression with Partially Shuffled LabelsMartin Slawski, Mostafa Rahmani, Ping Li 0001. 7 [doi]
• On Fast Convergence of Proximal Algorithms for SQRT-Lasso Optimization: Don't Worry About its Nonsmooth Loss FunctionXingguo Li, Haoming Jiang, Jarvis D. Haupt, Raman Arora, Han Liu 0001, Mingyi Hong, Tuo Zhao. 13 [doi]
• Correlated Learning for Aggregation SystemsTanvi Verma, Pradeep Varakantham. 14 [doi]
• Causal Calculus in the Presence of Cycles, Latent Confounders and Selection BiasPatrick Forré, Joris M. Mooij. 15 [doi]
• Variational Regret Bounds for Reinforcement LearningRonald Ortner, Pratik Gajane, Peter Auer. 16 [doi]
• Recommendation from Raw Data with Adaptive Compound Poisson FactorizationOlivier Gouvert, Thomas Oberlin, Cédric Févotte. 17 [doi]
• One-Shot Inference in Markov Random FieldsHao Xiong, Yuanzhen Guo, Yibo Yang, Nicholas Ruozzi. 19 [doi]
• Truly Proximal Policy OptimizationYuhui Wang, Hao He, Xiaoyang Tan. 21 [doi]
• Learning Factored Markov Decision Processes with UnawarenessCraig Innes, Alex Lascarides. 24 [doi]
• Expressive Priors in Bayesian Neural Networks: Kernel Combinations and Periodic FunctionsTim Pearce, Russell Tsuchida, Mohamed Zaki, Alexandra Brintrup, Andy Neely. 25 [doi]
• Countdown Regression: Sharp and Calibrated Survival PredictionsAnand Avati, Tony Duan, Sharon Zhou, Kenneth Jung, Nigam H. Shah, Andrew Y. Ng. 28 [doi]
• Reducing Exploration of Dying Arms in Mortal BanditsStefano Tracà, Weiyu Yan, Cynthia Rudin. 32 [doi]
• Comparing EM with GD in Mixture Models of Two ComponentsGuojun Zhang, Pascal Poupart, George Trimponias. 33 [doi]
• Efficient Search-Based Weighted Model IntegrationZhe Zeng, Guy Van den Broeck. 35 [doi]
• Causal Discovery with General Non-Linear Relationships using Non-Linear ICARicardo Pio Monti, Kun Zhang 0001, Aapo Hyvärinen. 45 [doi]
• BubbleRank: Safe Online Learning to Re-Rank via Implicit Click FeedbackChang Li 0003, Branislav Kveton, Tor Lattimore, Ilya Markov, Maarten de Rijke, Csaba Szepesvári, Masrour Zoghi. 47 [doi]
• Coordinating Users of Shared Facilities via Data-driven Predictive Assistants and Game TheoryPhilipp Geiger, Michel Besserve, Justus Winkelmann, Claudius Proissl, Bernhard Schölkopf. 49 [doi]
• The Incomplete Rosetta Stone problem: Identifiability results for Multi-view Nonlinear ICALuigi Gresele, Paul K. Rubenstein, Arash Mehrjou, Francesco Locatello, Bernhard Schölkopf. 53 [doi]
• Random Clique Covers for Graphs with Local Density and Global SparsitySinead A. Williamson, Mauricio Tec. 55 [doi]
• Randomized Iterative Algorithms for Fisher Discriminant AnalysisAgniva Chowdhury, Jiasen Yang, Petros Drineas. 64 [doi]
• Dynamic Trip-Vehicle Dispatch with Scheduled and On-Demand RequestsTaoan Huang, Bohui Fang, Xiaohui Bei, Fei Fang. 78 [doi]
• Fall of Empires: Breaking Byzantine-tolerant SGD by Inner Product ManipulationCong Xie, Oluwasanmi Koyejo, Indranil Gupta. 83 [doi]
• Adaptive Hashing for Model CountingJonathan Kuck, Tri Dao, Shenjia Zhao, Burak Bartan, Ashish Sabharwal, Stefano Ermon. 86 [doi]
• Towards a Better Understanding and Regularization of GAN Training DynamicsWeili Nie, Ankit Patel. 91 [doi]
• Domain Generalization via Multidomain Discriminant AnalysisShoubo Hu, Kun Zhang 0001, Zhitang Chen, Laiwan Chan. 101 [doi]
• Efficient Planning Under Uncertainty with Incremental RefinementJuan Carlos Saborío, Joachim Hertzberg. 112 [doi]
• Cubic Regularization with Momentum for Nonconvex OptimizationZhe Wang, Yi Zhou, Yingbin Liang, Guanghui Lan. 118 [doi]
• Stability of Linear Structural Equation Models of Causal InferenceKarthik Abinav Sankararaman, Anand Louis, Navin Goyal. 122 [doi]
• Random Sum-Product Networks: A Simple and Effective Approach to Probabilistic Deep LearningRobert Peharz, Antonio Vergari, Karl Stelzner, Alejandro Molina 0001, Martin Trapp, Xiaoting Shao, Kristian Kersting, Zoubin Ghahramani. 124 [doi]
• Towards Robust Relational Causal DiscoverySanghack Lee, Vasant G. Honavar. 127 [doi]
• The Role of Memory in Stochastic OptimizationAntonio Orvieto, Jonas Köhler, Aurélien Lucchi. 128 [doi]
• Random Search and Reproducibility for Neural Architecture SearchLiam Li, Ameet Talwalkar. 129 [doi]
• Joint Nonparametric Precision Matrix Estimation with ConfoundingSinong Geng, Mladen Kolar, Oluwasanmi Koyejo. 138 [doi]
• General Identifiability with Arbitrary Surrogate ExperimentsSanghack Lee, Juan D. Correa, Elias Bareinboim. 144 [doi]
• Differentiable Probabilistic Models of Scientific Imaging with the Fourier Slice TheoremKaren Ullrich, Rianne van den Berg, Marcus A. Brubaker, David J. Fleet, Max Welling. 148 [doi]
• Approximate Inference in Structured Instances with Noisy Categorical ObservationsAlireza Heidari, Ihab F. Ilyas, Theodoros Rekatsinas. 152 [doi]
• Randomized Value Functions via Multiplicative Normalizing FlowsAhmed Touati, Harsh Satija, Joshua Romoff, Joelle Pineau, Pascal Vincent. 156 [doi]
• A Fast Proximal Point Method for Computing Exact Wasserstein DistanceYujia Xie, Xiangfeng Wang, Ruijia Wang, Hongyuan Zha. 158 [doi]
• Neural Dynamics Discovery via Gaussian Process Recurrent Neural NetworksQi She, Anqi Wu. 159 [doi]
• Fisher-Bures Adversary Graph Convolutional NetworksKe Sun 0001, Piotr Koniusz, Zhen Wang. 161 [doi]
• Epsilon-BMC: A Bayesian Ensemble Approach to Epsilon-Greedy Exploration in Model-Free Reinforcement LearningMichael Gimelfarb, Scott Sanner, Chi-Guhn Lee. 162 [doi]
• Periodic Kernel Approximation by Index Set Fourier Series FeaturesAnthony Tompkins, Fabio Ramos. 163 [doi]
• Efficient Neural Network Verification with Exactness CharacterizationKrishnamurthy (Dj) Dvijotham, Robert Stanforth, Sven Gowal, Chongli Qin, Soham De, Pushmeet Kohli. 164 [doi]
• Augmenting and Tuning Knowledge Graph EmbeddingsRobert Bamler, Farnood Salehi, Stephan Mandt. 172 [doi]
• A Tighter Analysis of Randomised Policy IterationMeet Taraviya, Shivaram Kalyanakrishnan. 174 [doi]
• Perturbed-History Exploration in Stochastic Linear BanditsBranislav Kveton, Csaba Szepesvári, Mohammad Ghavamzadeh, Craig Boutilier. 176 [doi]
• An Improved Convergence Analysis of Stochastic Variance-Reduced Policy GradientPan Xu, Felicia Gao, Quanquan Gu. 191 [doi]
• Deep Mixture of Experts via Shallow EmbeddingXin Wang, Fisher Yu, Lisa Dunlap, Yi-An Ma, Ruth Wang, Azalia Mirhoseini, Trevor Darrell, Joseph E. Gonzalez. 192 [doi]
• Sampling-Free Variational Inference of Bayesian Neural Networks by Variance BackpropagationManuel Haussmann, Fred A. Hamprecht, Melih Kandemir. 193 [doi]
• Sliced Score Matching: A Scalable Approach to Density and Score EstimationYang Song, Sahaj Garg, Jiaxin Shi, Stefano Ermon. 204 [doi]
• Beyond Structural Causal Models: Causal Constraints ModelsTineke Blom, Stephan Bongers, Joris M. Mooij. 205 [doi]
• Be Greedy: How Chromatic Number meets Regret Minimization in Graph BanditsAadirupa Saha, Shreyas Sheshadri, Chiranjib Bhattacharyya. 206 [doi]
• Approximate Causal AbstractionsSander Beckers, Frederick Eberhardt, Joseph Y. Halpern. 210 [doi]
• The Sensitivity of Counterfactual Fairness to Unmeasured ConfoundingNiki Kilbertus, Philip J. Ball, Matt J. Kusner, Adrian Weller, Ricardo Silva. 213 [doi]
• Belief Propagation: Accurate Marginals or Accurate Partition Function - Where is the Difference?Christian Knoll, Franz Pernkopf. 221 [doi]
• Finding Minimal d-separators in Linear Time and ApplicationsBenito van der Zander, Maciej Liskiewicz. 222 [doi]
• A Bayesian Approach to Robust Reinforcement LearningEsther Derman, Daniel J. Mankowitz, Timothy A. Mann, Shie Mannor. 228 [doi]
• Adaptivity and Optimality: A Universal Algorithm for Online Convex OptimizationGuanghui Wang, Shiyin Lu, Lijun Zhang 0005. 232 [doi]
• Evacuate or Not? A POMDP Model of the Decision Making of Individuals in Hurricane Evacuation ZonesAdithya Raam Sankar, Prashant Doshi, Adam Goodie. 234 [doi]
• Probabilistic Programming for Birth-Death Models of Evolution Using an Alive Particle Filter with Delayed SamplingJan Kudlicka, Lawrence M. Murray, Fredrik Ronquist, Thomas B. Schön. 235 [doi]
• Variational Sparse CodingFrancesco Tonolini, Bjørn Sand Jensen, Roderick Murray-Smith. 239 [doi]
• Learning with Non-Convex Truncated Losses by SGDYi Xu, Shenghuo Zhu, Sen Yang, Chi Zhang, Rong Jin, Tianbao Yang. 244 [doi]
• Active Multi-Information Source Bayesian QuadratureAlexandra Gessner, Javier Gonzalez, Maren Mahsereci. 245 [doi]
• Cascading Linear Submodular Bandits: Accounting for Position Bias and Diversity in Online Learning to RankGaurush Hiranandani, Harvineet Singh, Prakhar Gupta, Iftikhar Ahamath Burhanuddin, Zheng Wen, Branislav Kveton. 248 [doi]
• Sinkhorn AutoEncodersGiorgio Patrini, Rianne van den Berg, Patrick Forré, Marcello Carioni, Samarth Bhargav, Max Welling, Tim Genewein, Frank Nielsen. 253 [doi]
• How to Exploit Structure while Solving Weighted Model Integration ProblemsSamuel Kolb, Pedro Zuidberg Dos Martires, Luc De Raedt. 262 [doi]
• Multi-Class Gaussian Process Classification Made Conjugate: Efficient Inference via Data AugmentationThéo Galy-Fajou, Florian Wenzel, Christian Donner, Manfred Opper. 264 [doi]
• A Flexible Framework for Multi-Objective Bayesian Optimization using Random ScalarizationsBiswajit Paria, Kirthevasan Kandasamy, Barnabás Póczos. 267 [doi]
• Efficient Multitask Feature and Relationship LearningHan Zhao 0002, Otilia Stretcu, Alexander J. Smola, Geoffrey J. Gordon. 275 [doi]
• Practical Multi-fidelity Bayesian Optimization for Hyperparameter TuningJian Wu, Saul Toscano-Palmerin, Peter I. Frazier, Andrew Gordon Wilson. 284 [doi]
• Adaptively Truncating Backpropagation Through Time to Control Gradient BiasChristopher Aicher, Nicholas J. Foti, Emily B. Fox. 290 [doi]
• Sampling-free Uncertainty Estimation in Gated Recurrent Units with Applications to Normative Modeling in NeuroimagingSeong Jae Hwang, Ronak Mehta, Hyunwoo J. Kim, Sterling C. Johnson, Vikas Singh. 296 [doi]
• Online Factorization and Partition of Complex Networks by Random WalkLin F. Yang, Zheng Yu, Vladimir Braverman, Tuo Zhao, Mengdi Wang. 299 [doi]
• On Densification for Minwise HashingTung Mai, Anup Rao, Matt Kapilevich, Ryan A. Rossi, Yasin Abbasi-Yadkori, Ritwik Sinha. 302 [doi]
• N-GCN: Multi-scale Graph Convolution for Semi-supervised Node ClassificationSami Abu-El-Haija, Amol Kapoor, Bryan Perozzi, Joonseok Lee. 310 [doi]
• Problem-dependent Regret Bounds for Online Learning with Feedback GraphsBingshan Hu, Nishant A. Mehta, Jianping Pan 0001. 312 [doi]
• Wasserstein Fair ClassificationRay Jiang, Aldo Pacchiano, Tom Stepleton, Heinrich Jiang, Silvia Chiappa. 315 [doi]
• Variational Training for Large-Scale Noisy-OR Bayesian NetworksGeng Ji 0001, Dehua Cheng, Huazhong Ning, Changhe Yuan, Hanning Zhou, Liang Xiong, Erik B. Sudderth. 317 [doi]
• Guaranteed Scalable Learning of Latent Tree ModelsFurong Huang, U. N. Niranjan, Ioakeim Perros, Robert Chen, Jimeng Sun, Anima Anandkumar. 319 [doi]
• On First-Order Bounds, Variance and Gap-Dependent Bounds for Adversarial BanditsRoman Pogodin, Tor Lattimore. 324 [doi]
• Noise Contrastive Priors for Functional UncertaintyDanijar Hafner, Dustin Tran, Timothy P. Lillicrap, Alex Irpan, James Davidson. 332 [doi]
• Fake It Till You Make It: Learning-Compatible Performance SupportJonathan Bragg, Emma Brunskill. 334 [doi]
• Literal or Pedagogic Human? Analyzing Human Model Misspecification in Objective LearningSmitha Milli, Anca D. Dragan. 335 [doi]
• Convergence Analysis of Gradient-Based Learning in Continuous GamesBenjamin Chasnov, Lillian J. Ratliff, Eric Mazumdar, Samuel Burden. 339 [doi]
• End-to-end Training of Deep Probabilistic CCA on Paired Biomedical ObservationsGregory Gundersen, Bianca Dumitrascu, Jordan T. Ash, Barbara E. Engelhardt. 340 [doi]
• Approximate Relative Value Learning for Average-reward Continuous State MDPsHiteshi Sharma, Mehdi Jafarnia-Jahromi, Rahul Jain 0002. 341 [doi]
• Exact Sampling of Directed Acyclic Graphs from Modular DistributionsTopi Talvitie, Aleksis Vuoksenmaa, Mikko Koivisto. 345 [doi]
• Intervening on Network TiesEli Sherman, Ilya Shpitser. 352 [doi]
• Generating and Sampling Orbits for Lifted Probabilistic InferenceSteven Holtzen, Todd D. Millstein, Guy Van den Broeck. 356 [doi]
• Real-Time Robotic Search using Structural Spatial Point ProcessesOlov Andersson, Per Sidén, Johan Dahlin, Patrick Doherty, Mattias Villani. 368 [doi]
• Social Reinforcement Learning to Combat Fake News SpreadMahak Goindani, Jennifer Neville. 370 [doi]
• P3O: Policy-on Policy-off Policy OptimizationRasool Fakoor, Pratik Chaudhari, Alexander J. Smola. 371 [doi]
• Causal Inference Under Interference And Network UncertaintyRohit Bhattacharya, Daniel Malinsky, Ilya Shpitser. 372 [doi]
• Revisiting Reweighted Wake-Sleep for Models with Stochastic Control FlowTuan Anh Le, Adam R. Kosiorek, N. Siddharth 0001, Yee Whye Teh, Frank Wood. 373 [doi]
• Learnability for the Information BottleneckTailin Wu, Ian Fischer, Isaac L. Chuang, Max Tegmark. 380 [doi]
• Learning Belief Representations for Imitation Learning in POMDPsTanmay Gangwani, Joel Lehman, Qiang Liu 0001, Jian Peng 0001. 383 [doi]
• Object Conditioning for Causal InferenceDavid D. Jensen, Javier Burroni, Matthew J. Rattigan. 393 [doi]
• CCMI : Classifier based Conditional Mutual Information EstimationSudipto Mukherjee, Himanshu Asnani, Sreeram Kannan. 403 [doi]
• Empirical Mechanism Design: Designing Mechanisms from DataEnrique Areyan Viqueira, Cyrus Cousins, Yasser Mohammad, Amy Greenwald. 406 [doi]
• On the Relationship Between Satisfiability and Markov Decision ProcessesRicardo Salmon, Pascal Poupart. 407 [doi]
• Interpretable Almost Matching Exactly With Instrumental VariablesM. Usaid Awan, Yameng Liu, Marco Morucci, Sudeepa Roy, Cynthia Rudin, Alexander Volfovsky. 410 [doi]
• Low Frequency Adversarial PerturbationChuan Guo, Jared S. Frank, Kilian Q. Weinberger. 411 [doi]
• Markov Logic Networks for Knowledge Base Completion: A Theoretical Analysis Under the MCAR AssumptionOndrej Kuzelka, Jesse Davis. 427 [doi]
• Identification In Missing Data Models Represented By Directed Acyclic GraphsRohit Bhattacharya, Razieh Nabi, Ilya Shpitser, James M. Robins. 428 [doi]
• A Weighted Mini-Bucket Bound for Solving Influence DiagramJunkyu Lee, Radu Marinescu 0002, Alexander Iher, Rina Dechter. 432 [doi]
• Subspace Inference for Bayesian Deep LearningPavel Izmailov, Wesley Maddox, Polina Kirichenko, Timur Garipov, Dmitry P. Vetrov, Andrew Gordon Wilson. 435 [doi]
• Off-Policy Policy Gradient with Stationary Distribution CorrectionYao Liu, Adith Swaminathan, Alekh Agarwal, Emma Brunskill. 440 [doi]
• Co-training for Policy LearningJialin Song, Ravi Lanka, Yisong Yue, Masahiro Ono. 441 [doi]
• Variational Inference of Penalized Regression with Submodular FunctionsKoh Takeuchi, Yuichi Yoshida, Yoshinobu Kawahara. 443 [doi]
• Probability Distillation: A Caveat and AlternativesChin-Wei Huang, Faruk Ahmed, Kundan Kumar, Alexandre Lacoste, Aaron C. Courville. 450 [doi]
• Bayesian Optimization with Binary Auxiliary InformationYehong Zhang, Zhongxiang Dai, Bryan Kian Hsiang Low. 468 [doi]
• On Open-Universe Causal ReasoningDuligur Ibeling, Thomas Icard. 481 [doi]
• Embarrassingly Parallel MCMC using Deep Invertible TransformationsDiego Mesquita, Paul Blomstedt, Samuel Kaski. 496 [doi]
• Fast Proximal Gradient Descent for A Class of Non-convex and Non-smooth Sparse Learning ProblemsYingzhen Yang, Jiahui Yu. 508 [doi]
• Block Neural Autoregressive FlowNicola De Cao, Wilker Aziz, Ivan Titov. 511 [doi]
• Exclusivity Graph Approach to Instrumental InequalitiesDavide Poderini, Rafael Chaves, Iris Agresti, Gonzalo Carvacho, Fabio Sciarrino. 512 [doi]